Overlap of high-risk individuals predicted by family history, genetic and non-genetic breast cancer risk prediction models: An analysis of 180,398 women across European and Asian ancestry populations

BackgroundBreast cancer is multifactorial. Focusing on limited risk factors may miss high-risk individuals. MethodsWe assessed the performance and overlap of various risk factors in identifying high-risk individuals for invasive breast cancer (BrCa) and ductal carcinoma in situ (DCIS) in 161,849 European-ancestry and 18,549 Asian-ancestry women. Discriminatory ability was evaluated using the area under the receiver operating characteristic curve (AUC). High-risk criteria included: 5-year absolute risk [&ge;]1{middle dot}66% by the Gail model [GAILbinary]; first-degree family history of breast cancer [FHbinary]; 5-year absolute risk [&ge;]1{middle dot}66% by a 313-variants polygenic risk score [PRSbinary]; and carriers of pathogenic variants in breast cancer predisposition genes [PTVbinary]. FindingsThe 5-year absolute risk by PRS outperformed the Gail model in predicting BrCa (Europeansvs controls: AUCPRS=0{middle dot}635 [0{middle dot}632-0{middle dot}638] vs AUCGail=0{middle dot}492 [0{middle dot}489-0{middle dot}495]; Asiansvs controls: AUCPRS=0{middle dot}564 [0{middle dot}556-0{middle dot}573] vs AUCGail=0{middle dot}506 [0{middle dot}497-0{middle dot}514]). PRSbinary and GAILbinary identified more high-risk European than Asia individuals. High-risk proportions were higher among BrCa (16-26%) and DCIS (20-33%) compared to controls (9-15%) among young Europeans and all Asians. Fewer than 7% of BrCa, 10% of DCIS, and 3% of controls were classified as high-risk by multiple risk classifiers. Overlap between PRSbinary and PTVbinary was minimal (<0{middle dot}65% Europeans, <0{middle dot}15% Asians) compared to the proportion at high risk using PTVbinary alone (Europeans: 4{middle dot}6%, Asians: 4{middle dot}4%) and PRSbinary alone (Europeans: 13{middle dot}9%, Asians: 8{middle dot}5%). PRSbinary and FHbinary uniquely identified 5-6% and 9-11% of young BrCa, respectively. InterpretationThe incomplete overlap between high-risk individuals identified by PRSbinary, GAILbinary, FHbinary, and PTVbinary highlights the need for a comprehensive approach to breast cancer risk prediction. SIGNIFICANCEThis study shows that different ways of predicting breast cancer risk do not always flag the same people, suggesting that combining multiple risk factors could improve early detection and screening.